This invention generally relates to social networking systems, and more particularly to recommending objects or pages to new users of the social networking system.
A social networking system allows its users to connect to and interact with other social networking system users and with objects on the social networking system. As a user on a social networking system interacts with various objects (e.g., pages for businesses, content items posted on the social networking system, profiles of users on the social networking system, etc.), the user develops a history of interacting with objects. This interaction history also provides information about a user, including the user's interests. Based on these types of information associated with a user, the social networking system may recommend objects or pages to the user, encouraging the user to interact with the recommended objects. For example, if a user has “liked” or become a fan of certain types of pages on the social networking system in the past, the social networking system can recommend pages to that user that are similar to the ones the user has previously “liked.”
However, for users new to the social networking system or with little or no information regarding tastes, preferences or connections, the social networking system is often unable to generate accurate recommendations of objects to provide to the users. Modern recommender systems that are often used by social networking systems typically use three types of recommendation strategies; user-user, item-item, and user-item. Each of these systems requires a model of a user to derive recommendations. For user-user recommender systems, the model must provide a similarity measurement between users. And for both item-item and user-item, the model must provide a set of previously rated entities for user. None of these foundations supports generating recommendations for a new users with little to no information stored in the social networking system. Hence users with little or no information stored with the social networking system provide a challenge for recommendation systems. This is sometimes referred to as the cold-start problem.